PyTorch splits hardware integration into four orthogonal abstractions (device, memory allocator, stream, compiler), and only when all four layers are implemented can a device be correctly treated by PyTorch's mechanisms such as automatic differentiation, caching allocation, asynchronous execution, and graph capture.